Academic literature on the topic 'MR-guided radiotherapy'

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Journal articles on the topic "MR-guided radiotherapy"

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Slotman, B., and C. Gani. "Online MR-guided radiotherapy – A new era in radiotherapy." Clinical and Translational Radiation Oncology 18 (September 2019): 102–3. http://dx.doi.org/10.1016/j.ctro.2019.04.011.

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Jonsson, J. "SP-0006: Challenges in MR guided radiotherapy." Radiotherapy and Oncology 119 (April 2016): S2—S3. http://dx.doi.org/10.1016/s0167-8140(16)31255-5.

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van den Berg, Cornelius. "[I186] New technologies for MR guided radiotherapy." Physica Medica 52 (August 2018): 71. http://dx.doi.org/10.1016/j.ejmp.2018.06.258.

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Pollard, Julianne M., Zhifei Wen, Ramaswamy Sadagopan, Jihong Wang, and Geoffrey S. Ibbott. "The future of image-guided radiotherapy will be MR guided." British Journal of Radiology 90, no. 1073 (May 2017): 20160667. http://dx.doi.org/10.1259/bjr.20160667.

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Palacios, M. A., O. Bohoudi, S. Senan, B. Slotman, A. Bruynzeel, and F. J. Lagerwaard. "1. MR-guided adaptive stereotactic radiotherapy: A new paradigm in radiotherapy." Physica Medica 44 (December 2017): 1. http://dx.doi.org/10.1016/j.ejmp.2017.10.026.

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Jaffray, D. "SP-0395: Challenges associated with MR guided radiotherapy." Radiotherapy and Oncology 123 (May 2017): S211. http://dx.doi.org/10.1016/s0167-8140(17)30837-x.

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Rodriguez, Lori L., Rupesh Kotecha, Martin C. Tom, Michael D. Chuong, Jessika A. Contreras, Tino Romaguera, Diane Alvarez, et al. "CT-guided versus MR-guided radiotherapy: Impact on gastrointestinal sparing in adrenal stereotactic body radiotherapy." Radiotherapy and Oncology 166 (January 2022): 101–9. http://dx.doi.org/10.1016/j.radonc.2021.11.024.

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Song, Yajun, Zhenjiang Li, Huadong Wang, Yun Zhang, and Jinbo Yue. "MR-LINAC-Guided Adaptive Radiotherapy for Gastric MALT: Two Case Reports and a Literature Review." Radiation 2, no. 3 (July 13, 2022): 259–67. http://dx.doi.org/10.3390/radiation2030019.

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It is still very challenging to use conventional radiation therapy techniques to treat stomach tumors, although image-guided radiotherapy, mainly by kV X-ray imaging techniques, has become routine in the clinic. This is because the stomach is one of the most deformable organs, and thus it is vulnerable to respiratory motions, daily diet, and body position changes. In addition, X-ray radiographs and CT volumetric images have low contrast in soft tissues. In contrast, magnetic resonance imaging (MRI) techniques provide good contrast in images of soft tissues. The emerging MR-guided radiotherapy, based on the MR-LINAC system, may have the potential to solve the above difficulties due to its unique advantages. The real-time imaging feature and the high-contrast of soft tissues MR images provided by the MR-LINAC system have facilitated the therapeutic adaptive planning. Online learning capabilities could be used to optimize the automatic delineation of the target organ or tissue prior to each radiotherapy session. This could greatly improve the accuracy and efficiency of the target delineation in adaptive planning. In this clinical case report, we elaborated a workflow for the diagnosis and treatment of two patients with gastric mucosa-associated lymphoid tissue (MALT) lymphoma. One patient underwent MR-guided daily adaptive radiotherapy based on daily automated segmentation using the novel artificial intelligence (AI) technique for gastric delineation.
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Fahad, H. M., S. Dorsch, M. Zaiß, and C. P. Karger. "PO-1638 Multiparametric optimization of MR imaging sequences for MR guided radiotherapy." Radiotherapy and Oncology 170 (May 2022): S1433—S1434. http://dx.doi.org/10.1016/s0167-8140(22)03602-7.

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Schumacher, Leif-Erik D., Alan Dal Pra, Sarah E. Hoffe, and Eric A. Mellon. "Toxicity reduction required for MRI-guided radiotherapy to be cost-effective in the treatment of localized prostate cancer." British Journal of Radiology 93, no. 1114 (October 1, 2020): 20200028. http://dx.doi.org/10.1259/bjr.20200028.

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Objective: To determine the toxicity reduction required to justify the added costs of MRI-guided radiotherapy (MR-IGRT) over CT-based image guided radiotherapy (CT-IGRT) for the treatment of localized prostate cancer. Methods: The costs of delivering prostate cancer radiotherapy with MR-IGRT and CT-IGRT in conventional 39 fractions and stereotactic body radiotherapy (SBRT) 5 fractions schedules were determined using literature values and cost accounting from two institutions. Gastrointestinal and genitourinary toxicity rates associated with CT-IGRT were summarized from 20 studies. Toxicity-related costs and utilities were obtained from literature values and cost databases. Markov modeling was used to determine the savings per patient for every 1% relative reduction in acute and chronic toxicities by MR-IGRT over 15 years. The costs and quality adjusted life years (QALYs) saved with toxicity reduction were juxtaposed with the cost increase of MR-IGRT to determine toxicity reduction thresholds for cost-effectiveness. One way sensitivity analyses were performed. Standard $100,000 and $50,000 per QALY ratios were used. Results: The added cost of MR-IGRT was $1,459 per course of SBRT and $10,129 per course of conventionally fractionated radiotherapy. Relative toxicity reductions of 7 and 14% are required for SBRT to be cost-effective using $100,000 and $50,000 per QALY, respectively. Conventional radiotherapy requires relative toxicity reductions of 50 and 94% to be cost-effective. Conclusion: From a healthcare perspective, MR-IGRT can reasonably be expected to be cost-effective. Hypofractionated schedules, such a five fraction SBRT, are most likely to be cost-effective as they require only slight reductions in toxicity (7–14%). Advances in knowledge: This is the first detailed economic assessment of MR-IGRT, and it suggests that MR-IGRT can be cost-effective for prostate cancer treatment through toxicity reduction alone.
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Dissertations / Theses on the topic "MR-guided radiotherapy"

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Schellhammer, Sonja. "Technical Feasibility of MR-Integrated Proton Therapy: Beam Deflection and Image Quality." 2019. https://tud.qucosa.de/id/qucosa%3A34132.

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Es wird erwartet, dass die Integration der Magnetresonanztomografie (MRT) in die Protonentherapie die Treffgenauigkeit bei der Strahlentherapie für Krebserkrankungen deutlich verbessern wird. Besonders für Tumoren in beweglichen Organen des Thorax oder des Abdomens könnte die MRT-integrierte Protonentherapie (MRiPT) eine Synchronisierung der Bestrahlung mit der Tumorposition ermöglichen, was zu einer verminderten Normalgewebsdosis und weniger Nebenwirkungen führen könnte. Bis heute ist solch eine Integration jedoch aufgrund fehlender Studien zu potenziellen gegenseitigen Störeinflüssen dieser beiden Systeme nicht vollzogen worden. Diese Arbeit widmete sich zwei solcher Störeinflüsse, und zwar der Ablenkung des Protonenstrahls im Magnetfeld des MRT- Scanners, und umgekehrt, dem Einfluss der elekromagnetischen Felder der Protonentherapieanlage und des Protonenstrahls selbst auf die MRT-Bilder. Obwohl vorangegangene Studien den derzeitigen Konsens aufgezeigt haben, dass die Trajektorie eines abgebremsten Protonenstrahls im homogenen Phantom in einem transversalen Magnetfeld vorhersagbar ist, zeigte sich im quantitativen Vergleich der publizierten Modelle, der im ersten Teil dieser Arbeit vorgestellt wurde, dass die Vorhersagen dieser Modelle nur für eine begrenzte Anzahl von Kombinationen aus Magnetfeldstärke und Protonenenergie übereinstimmen. Die Schwächen bestehender analytischer Modelle wurden deshalb analysiert und quantifiziert. Kritische Annahmen und die mangelnde Anwendbarkeit auf realistische, d.h. inhomogene Magnetfeldstärken und Patientengeometrien wurden als Hauptprobleme identifiziert. Um diese zu überwinden, wurde ein neues semianalytisches Modell namens RAMDIM entwickelt. Es wurde gezeigt, dass dieses auf realistischere Fälle anwendbar und genauer ist als existierende analytische Modelle und dabei schneller als Monte-Carlo-basierte Teilchenspursimulationen. Es wird erwartet, dass dieses Modell in der MRiPT Anwendung findet zur schnellen und genauen Ablenkungsberechnung, zur Betrahlungsplanoptimierung und bei der MRT-geführten Strahlnachführung. In einem zweiten Schritt wurde die magnetfeldinduzierte Protonenstrahlablenkung in einem gewebeähnlichen Material durch Filmdosimetrie erstmalig gemessen und mit Monte-Carlo-Simulationen verglichen. In einem transversalen Magnetfeld einer Flussdichte von 0,95 T wurde experimentell gezeigt, dass die laterale Versetzung des Bragg-Peaks für Protonenenergien zwischen 80 und 180 MeV in PMMA zwischen 1 und 10 mm liegt. Die Retraktion des Bragg-Peaks war ≤ 0,5 mm. Es wurde gezeigt, dass die gemessene Versetzung des Bragg-Peaks innerhalb von 0,8 mm mit Monte-Carlo-basierten Vorhersagen übereinstimmt. Diese Ergebnisse weisen darauf hin, dass die Protonenstrahlablenkung durch Monte-Carlo-Simulationen genau vorhersagbar ist und damit der Realisierbarkeit der MRiPT nicht im Wege steht. Im zweiten Teil dieser Arbeit wurde erstmalig ein MRT-Scanner in eine Protonenstrahlführung integriert. Hierfür wurde ein offener Niederfeld-MRT-Scanner am Ende einer statischen Forschungsstrahlführung einer Protonentherapieanlage platziert. Die durch das statische Magnetfeld des MRT-Scanners hervorgerufene Strahlablenkung wurde bei der Ausrichtung des MRT-Scanners berücksichtigt. Die sequenzabhängigen, veränderlichen Gradientenfelder hatten keinen messbaren Einfluss auf das transversale Strahlprofil hinter dem MRT-Scanner. Die Magnetfeldhomogenität des Scanners lag innerhalb der Herstellervorgaben und zeigte keinen relevanten Einfluss von Rotationen der Protonengantry im benachbarten Bestrahlungsraum. Eine magnetische Abschirmung war zum gleichzeitigen Betrieb des MRT-Scanners und der Protonentherapieanlage nicht notwendig. Dies beweist die Machbarkeit gleichzeitiger Bestrahlung und Bildgebung in einem ersten MRiPT Aufbau. Die MRT-Bildqualität des Aufbaus wurde darauffolgend anhand eines angepassten Standardprotokolls aus Spin-Echo- und Gradienten-Echo-Sequenzen quantifiziert und es wurde gezeigt, dass die Bildqualität sowohl ohne als auch mit gleichzeitiger Bestrahlung hinreichend ist. Alle bestimmten geometrischen Parameter stimmten mit den physikalischen Abmessungen des verwendeten Phantoms innerhalb eines Bildpixels überein. Wie es für Niederfeld-MRT-Scanner üblich ist, war das Signal-Rausch-Verhältnis (SNR) der MRT-Bilder gering, was im Vergleich zu den Standardkriterien zu einer geringen Bildhomogenität und zu einem hohen Geisterbildanteil im Bild führte. Außerdem wurde aufgrund von Unsicherheiten in der Hochfrequenzkalibrierung des MRT-Scanners eine starke Schwankung der vertikalen Phantomposition mit einem Interquartilabstand von bis zu 1,5 mm beobachtet. T2*-gewichtete Gradientenechosequenzen zeigten zudem aufgrund von Magnetfeldinho- mogenitäten relevante ortsabhängige Bildverzerrungen. Es wurde gezeigt, dass die meisten Bildqualitätsparameter mit und ohne gleichzeitige Betrahlung äquivalent sind. Es wurde jedoch ein signifikanter Betrahlungseinfluss in Form von einer vertikalen Bildverschiebung und einer Verminderung des SNR beobachtet, die durch eine Änderung im Magnetfeld des MRT-Scanners erklärt werden können, welche durch zu diesem Feld parallel ausgerichtete Komponenten im Fernfeld der Strahlführungsmagneten hervorgerufen wird. Während das verminderte SNR vermutlich irrelevant ist (Dif- ferenz im Median ≤ 1,5), ist die sequenzabhängige Bildverschiebung (Differenz im Median bis zu 0,7 mm) nicht immer vernachlässigbar. Diese Ergebisse zeigen, dass die MRT-Bilder durch gleichzeitige Bildgebung nicht schwerwiegend verfälscht werden, dass aber eine dedizierte Optimierung der Hochfrequenzkalibrierung und der MRT-Bildsequenzen notwendig ist. Im letzten Teil der Arbeit wurde gezeigt, dass ein stromabhängiger Einfluss des Protonenstrahls auf MRT-Bilder eines Wasserphantoms durch zwei verschiedene MRT-Sequenzen messbar gemacht und zur Reichweiteverifikation genutzt werden kann. Der Effekt war in verschiedenen Flüssigkeiten, jedoch nicht in viskosen und festen Materialen, nachweisbar und wurde auf Hitzekonvektion zurückgeführt. Es wird erwartet, dass diese Methode in der MRiPT für Konstanztests der Protonenreichweite bei der Maschinenqualitätssicherung nützlich sein wird. Zusammenfassend hat diese Arbeit die Genauigkeit der Vorhersage der Strahlablenkung quantifiziert und verbessert, sowie Potenzial und Realisierbarkeit einer gleichzeitigen MRT-Bildgebung und Protonenbestrahlung gezeigt. Die weitere Entwicklung eines ersten MRiPT-Prototyps ist demnach gerechtfertigt.:List of Figures v List of Tables vii 1 General Introduction 1 2 State of the Art: Proton Therapy and Magnetic Resonance Imaging 3 2.1 Proton Therapy 4 2.1.1 Physical Principle 4 2.1.2 Beam Delivery 7 2.1.3 Motion Management and the Role of Image Guidance 10 2.2 Magnetic Resonance Imaging 14 2.2.1 Physical Principle 14 2.2.2 Image Generation by Pulse Sequences 18 2.2.3 Image Quality 21 2.3 MR-Guided Radiotherapy 24 2.3.1 Offline MR Guidance 24 2.3.2 On-line MR Guidance 25 2.4 MR-Integrated Proton Therapy 28 2.4.1 Aims of this Thesis 32 3 Magnetic Field-Induced Beam Deflection and Bragg Peak Displacement 35 3.1 Analytical Description 36 3.1.1 Review of Analytical Models 36 3.1.2 New Model Formulation 41 3.1.3 Evaluation of Analytical and Numerical Models 44 3.1.4 Discussion 51 3.2 Monte Carlo Simulation and Experimental Verification 54 3.2.1 Verification Setup 54 3.2.2 Monte Carlo Simulation 56 3.2.3 Experimental Verification 60 3.2.4 Discussion 61 3.3 Summary 63 4 Integrated In-Beam MR System: Proof of Concept 65 4.1 Integration of a Low-Field MR Scanner and a Static Research Beamline 65 4.1.1 Proton Therapy System 66 4.1.2 MR Scanner 66 4.1.3 Potential Sources of Interference 67 4.1.4 Integration of Both Systems 68 4.2 Beam and Image Quality in the Integrated Setup 70 4.2.1 Beam Profile 70 4.2.2 MR Magnetic Field Homogeneity 72 4.2.3 MR Image Quality - Qualitative In Vivo and Ex Vivo Test 74 4.2.4 MR Image Quality - Quantitative Phantom Tests 77 4.3 Feasibility of MRI-based Range Verification 86 4.3.1 MR Sequences 86 4.3.2 Proton Beam Parameters 88 4.3.3 Target Material Dependence 91 4.3.4 Discussion 92 4.4 Summary 96 5 Discussion and Future Perspectives 99 6 Summary/Zusammenfassung 105 6.1 Summary 105 6.2 Zusammenfassung 108 Bibliography I Supplementary Information XXIX A Beam Deflection: Experimental Measurements XXIX A.1 Setup XXIX A.2 Film Handling and Evaluation XXX A.3 Uncertainty Estimation XXX B Beam Deflection: Monte Carlo Simulations XXXIII B.1 Magnetic Field Model XXXIII B.2 Uncertainty Estimation XXXIV C Integrated MRiPT Setup XXXVI C.1 Magnetic Field Map XXXVI C.2 Sequence Parameters XXXVI C.3 Image Quality Parameters XLII C.4 Range Verification Sequences XLII
The integration of magnetic resonance imaging (MRI) into proton therapy is expected to strongly increase the targeting accuracy in radiation therapy for cancerous diseases. Especially for tumours situated in mobile organs in the thorax and abdomen, MR-integrated proton therapy (MRiPT) could enable the synchronisation of irradiation to the tumour position, resulting in less dose to normal tissue and reduced side effects. However, such an integration has been hindered so far by a lack of scientific studies on the potential mutual interference between the two components. This thesis was dedicated to two of these sources of interference, namely the deflection of the proton beam by the magnetic field of the MR scanner and, vice versa, alterations of the MR image induced by the electromagnetic fields of the proton therapy facility and by the beam itself. Although previous work has indicated that there is general consensus that the trajectory of a slowing down proton beam in a homogeneous phantom inside a transverse magnetic field is predictable, a quantitative comparison of the published methods, as presented in the first part of this thesis, has shown that predictions of different models only agree for certain proton beam energies and magnetic flux densities. Therefore, shortcomings of previously published analytical methods have been analysed and quantified. The inclusion of critical assumptions and the lack of applicability to realistic, i.e. non-uniform, magnetic flux densities and patient anatomies have been identified as main problems. To overcome these deficiencies, a new semi-analytical model called RAMDIM has been developed. It was shown that this model is both applicable to more realistic setups and less assumptive than existing analytical approaches, and faster than Monte Carlo based particle tracking simulations. This model is expected to be useful in MRiPT for fast and accurate deflection estimations, treatment plan optimisation, and MR-guided beam tracking. In a second step, the magnetic field-induced proton beam deflection has been measured for the first time in a tissue-mimicking medium by film dosimetry and has been compared against Monte Carlo simulations. In a transverse magnetic field of 0.95 T, it was experimentally shown that the lateral Bragg peak displacement ranges between 1 mm and 10 mm for proton energies between 80 and 180 MeV in PMMA. Range retraction was found to be ≤ 0.5 mm. The measured Bragg peak displacement was shown to agree within 0.8 mm with Monte Carlo simulations. These results indicate that proton beam deflection in a homogeneous medium is accurately predictable for intermediate proton beam energies and magnetic flux densities by Monte Carlo simulations and therefore not impeding the feasibility of MRiPT. In the second part of this thesis, an MR scanner has been integrated into a proton beam line for the first time. For this purpose, an open low-field MR scanner has been placed at the end of a fixed horizontal proton research beam line in a proton therapy facility. The beam deflection induced by the static magnetic field of the scanner was taken into account for alignment of the beam and the FOV of the scanner. The pulse sequence-dependent dynamic gradient fields did not measurably affect the transverse beam profile behind the MR scanner. The MR magnetic field homogeneity was within the vendor’s specifications and not relevantly influenced by the rotation of the proton gantry in the neighbouring treatment room. No magnetic field compensation system was required for simultaneous operation of the MR scanner and the proton therapy system. These results proof that simultaneous irradiation and imaging is feasible in an in-beam MR setup. The MR image quality of the in-beam MR scanner was then quantified by an adapted standard protocol comprising spin and gradient echo imaging and shown to be acceptable both with and without simultaneous proton beam irradiation. All geometrical parameters agreed with the mechanical dimensions of the used phantom within one pixel width. As common for low-field MR scanners, the signal-to-noise ratio (SNR) of the MR images was low, which resulted in a low image uniformity and a high ghosting ratio in comparison to the standardised test criteria. Furthermore, a strong fluctuation of the vertical phantom position due to uncertainties in the pre-scan frequency calibration was observed, with an interquartile range of up to 1.5 mm. T2*-weighted gradient echo images showed relevant nonuniform deformations due to magnetic field inhomogeneities. Most image quality parameters were shown to be equivalent with and without simultaneous proton beam irradiation. However, a significant influence of simultaneous irradiation was observed as a shift of the vertical phantom position and a decrease in the SNR, both of which can be explained by a change in the B0 field of the MR scanner induced by components of the fringe field of the beam line magnets directed parallel to B0 . While the decrease in SNR is not expected to be relevant (median differences were within 1.5 ), the sequence-dependent phantom shift (median differences of up to 0.7 mm) can become non-negligible. These results show that the MR images are not severely distorted by simultaneous irradiation, but a dedicated optimisation of the pre-scan RF calibration and the MR sequences is required for MRiPT. Lastly, a current-dependent influence of the proton beam on the MR image was shown to be measurable in water in two different MR sequences, which allowed for range verification measurements. The effect was observed in different liquids but not in highly viscose and solid materials, and most probably induced by heat convection. This method is expected to be useful in MRiPT for consistency tests of the proton range during machine-specific quality assurance. In conclusion, this work has improved and quantified the accuracy of beam deflection predictions and shown the feasibility and potential of in-beam MR imaging, justifying further research towards a first MRiPT prototype.:List of Figures v List of Tables vii 1 General Introduction 1 2 State of the Art: Proton Therapy and Magnetic Resonance Imaging 3 2.1 Proton Therapy 4 2.1.1 Physical Principle 4 2.1.2 Beam Delivery 7 2.1.3 Motion Management and the Role of Image Guidance 10 2.2 Magnetic Resonance Imaging 14 2.2.1 Physical Principle 14 2.2.2 Image Generation by Pulse Sequences 18 2.2.3 Image Quality 21 2.3 MR-Guided Radiotherapy 24 2.3.1 Offline MR Guidance 24 2.3.2 On-line MR Guidance 25 2.4 MR-Integrated Proton Therapy 28 2.4.1 Aims of this Thesis 32 3 Magnetic Field-Induced Beam Deflection and Bragg Peak Displacement 35 3.1 Analytical Description 36 3.1.1 Review of Analytical Models 36 3.1.2 New Model Formulation 41 3.1.3 Evaluation of Analytical and Numerical Models 44 3.1.4 Discussion 51 3.2 Monte Carlo Simulation and Experimental Verification 54 3.2.1 Verification Setup 54 3.2.2 Monte Carlo Simulation 56 3.2.3 Experimental Verification 60 3.2.4 Discussion 61 3.3 Summary 63 4 Integrated In-Beam MR System: Proof of Concept 65 4.1 Integration of a Low-Field MR Scanner and a Static Research Beamline 65 4.1.1 Proton Therapy System 66 4.1.2 MR Scanner 66 4.1.3 Potential Sources of Interference 67 4.1.4 Integration of Both Systems 68 4.2 Beam and Image Quality in the Integrated Setup 70 4.2.1 Beam Profile 70 4.2.2 MR Magnetic Field Homogeneity 72 4.2.3 MR Image Quality - Qualitative In Vivo and Ex Vivo Test 74 4.2.4 MR Image Quality - Quantitative Phantom Tests 77 4.3 Feasibility of MRI-based Range Verification 86 4.3.1 MR Sequences 86 4.3.2 Proton Beam Parameters 88 4.3.3 Target Material Dependence 91 4.3.4 Discussion 92 4.4 Summary 96 5 Discussion and Future Perspectives 99 6 Summary/Zusammenfassung 105 6.1 Summary 105 6.2 Zusammenfassung 108 Bibliography I Supplementary Information XXIX A Beam Deflection: Experimental Measurements XXIX A.1 Setup XXIX A.2 Film Handling and Evaluation XXX A.3 Uncertainty Estimation XXX B Beam Deflection: Monte Carlo Simulations XXXIII B.1 Magnetic Field Model XXXIII B.2 Uncertainty Estimation XXXIV C Integrated MRiPT Setup XXXVI C.1 Magnetic Field Map XXXVI C.2 Sequence Parameters XXXVI C.3 Image Quality Parameters XLII C.4 Range Verification Sequences XLII
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Books on the topic "MR-guided radiotherapy"

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Kerkmeijer, Linda G. W., Clifton D. Fuller, Ben Slotman, and Vincenzo Valentini, eds. Online Adaptive MR-guided Radiotherapy. Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88971-503-9.

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Book chapters on the topic "MR-guided radiotherapy"

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Lacornerie, Thomas, Albert Lisbona, and Andrew W. Beavis. "CyberKnife, TomoTherapy and MR-Guided Linear Accelerators." In Handbook of Radiotherapy Physics, Vol1:281—Vol1:294. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780429201493-17.

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Vázquez Romaguera, Liset, Tal Mezheritsky, and Samuel Kadoury. "Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 238–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87202-1_23.

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Lu, Chao, Sudhakar Chelikani, and James S. Duncan. "A Unified Framework for Joint Segmentation, Nonrigid Registration and Tumor Detection: Application to MR-Guided Radiotherapy." In Lecture Notes in Computer Science, 525–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22092-0_43.

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Neph, Ryan, Yangsibo Huang, Youming Yang, and Ke Sheng. "DeepMCDose: A Deep Learning Method for Efficient Monte Carlo Beamlet Dose Calculation by Predictive Denoising in MR-Guided Radiotherapy." In Artificial Intelligence in Radiation Therapy, 137–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32486-5_17.

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Pen, Olga, Borna Maraghechi, Lauren Henke, and Olga Green. "MR-Integrated Linear Accelerators: First Clinical Results." In Image-Guided High-Precision Radiotherapy, 159–77. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08601-4_7.

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Morris, Eric D., Dylan P. O’Connell, Yu Gao, and Minsong Cao. "MR safety considerations for MRI-guided radiotherapy." In Advances in Magnetic Resonance Technology and Applications, 81–100. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-91689-9.00005-4.

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Lavender, Frances. "Imaging for treatment delivery: Image-guided radiotherapy." In Physics for Clinical Oncology, 163—C10.F5. 2nd ed. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/med/9780198862864.003.0010.

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Abstract This chapter, ‘Imaging for treatment delivery: Image-guided radiotherapy’, discusses the technology and workflows used to verify the geometric accuracy of treatment delivery. A review of the relevant photon interaction processes (photoelectric effect and Compton scattering) precedes a discussion on cone beam CT imaging (CBCT), how this differs from fan-beam CT imaging and how it is used in clinical practice. The importance of patient positioning is highlighted. Other techniques used to improve treatment accuracy, such as gating and tracking are described. The use of adaptive radiotherapy is outlined and the chapter closes with a brief introduction to the possibilities presented by MR-linac technology.
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Camilleri, Philip, Andy Gaya, Veni Ezhil, and James Good. "Patient reported outcomes in the use of MR-guided radiotherapy." In Advances in Magnetic Resonance Technology and Applications, 483–90. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-91689-9.00023-6.

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Gani, Cihan, Luca Boldrini, Vincenzo Valentini, and Daniel Zips. "Online MR-guided radiotherapy in rectal cancer—Dose escalation and beyond." In Advances in Magnetic Resonance Technology and Applications, 367–73. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-91689-9.00018-2.

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Michalet, Morgan, Simon Valdenaire, Karl Bordeau, David Azria, and Olivier Riou. "MR-guided radiotherapy for liver tumors: Hepatocarcinomas, cholangiocarcinomas, and liver metastases." In Advances in Magnetic Resonance Technology and Applications, 295–314. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-91689-9.00015-7.

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Conference papers on the topic "MR-guided radiotherapy"

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Hughes, Sophie, Simone Lanfredini, Asmita Thappa, Somnath Mukherjee, and Eric O’Neill. "Abstract B69: Assessment of CCR5/maraviroc immunotherapy in combination with PD1 and MR-guided radiotherapy for treatment of pancreatic cancer." In Abstracts: AACR Special Conference on Tumor Immunology and Immunotherapy; November 17-20, 2019; Boston, MA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/2326-6074.tumimm19-b69.

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Lanfredini, Simone, Sophie Hughes, Asmita Thapa, Fiona Bangs, Jennifer Morton, Danny Allen, Veerle Kersemans, et al. "Abstract B30: Assessment of CCR5i/maraviroc immunotherapy in combination with PD1 and MR-guided radiotherapy for treatment of pancreatic cancer." In Abstracts: AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; September 6-9, 2019; Boston, MA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.panca19-b30.

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Reports on the topic "MR-guided radiotherapy"

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Chen, Lili. MR-Guided Pulsed High-Intensity Focused Ultrasound Enhancement of Gene Therapy Combined With Androgen Deprivation and Radiotherapy for Prostate Cancer Treatment. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada518248.

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Chen, Lili. MR Guided Pulsed High Intensity Focused Ultrasound Enhancement of Gene Therapy Combined with Androgen Deprivation and Radiotherapy for Prostate Cancer Treatment. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada569443.

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